Multiple Principal Wicked Problems, Strategic Imports, Innovations & EMF Export Performances
Bibliographic record
Abstract
In this paper, we investigate how multiple principal wicked problems (MPWP) adversely affect the export performance of emerging market firms (EMFs). EMF exports primarily depend on either of two export strategies, namely, (i) innovative capabilities or, more importantly, (ii) import of critical components from developed economies. The dependence of emerging markets, in general, on strategic imports is often attributed to the legacy of resource constraints and technological limitations from a colonial past. The choice to adopt either or both of the export strategies for export performance, depends on the conflicting objectives cum influence of the dominant investors. Empirically modelling a panel data of 2171 Indian firms over 31 years (1988 – 2019), we highlight that for EMFs, when exposed to multiple principals with conflicting objectives, the said choice becomes wickedly problematic. That, in turn, adversely affects the export performance of EMFs. Our study on MPWP complements the agency perspective and calls for further investigation into specific governance mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".